I am a final year Ph.D. candidate in the College of Information and Computer Sciences at University of Massachusetts Amherst. I have received Dissertation Writing Fellowship for my Ph.D. thesis.
I am co-advised by Prof. Andrew McGregor and Prof. Cameron Musco.
Prior to this, I completed my undergraduate in Computer Science at IIT Madras in 2016.
From January-May 2022, I am participating in the Causality program at the Simons Institute for the Theory of Computing, located on the UC Berkeley campus.
I will be joining Adobe Research (San Jose) as a Research Scientist in June 2022.
Contact Email: raddanki AT cs.umass.edu
Linkedin, Google Scholar, Twitter
I am broadly interested in the design and analysis of algorithms for data science. Recently, I have been working on identifying connections between discrete optimization and causal inference.
(author ordering for the papers below is alphabetical unless marked *)
- Sample Constrained Treatment Effect Estimation
Raghavendra Addanki, David Arbour, Tung Mai, Cameron Musco, and Anup Rao
- Improved Approximation and Scalability for Fair Max-Min Diversification
Raghavendra Addanki, Andrew McGregor, Alexandra Meliou, and Zafeiria Moumoulidou
International Conference on Database Theory (ICDT) 2022.
- Collaborative Causal Discovery with Atomic Interventions
Raghavendra Addanki, Shiva Prasad Kasiviswanathan
Neural Information Processing Systems (NeurIPS) 2021.
- Intervention Efficient Algorithms for Approximate Learning of Causal Graphs
Raghavendra Addanki, Andrew McGregor, Cameron Musco
Algorithmic Learning Theory (ALT) 2021
[arXiv, proceedings][1hr video at MIT,12 min video at ALT]
- How to Design Robust Algorithms using Noisy Comparison Oracle
Raghavendra Addanki, Sainyam Galhotra, Barna Saha
International Conference on Very Large Data Bases (VLDB) 2021
- Efficient Intervention Design for Causal Discovery with Latents
Raghavendra Addanki, Shiva Prasad Kasiviswanathan, Andrew McGregor, Cameron Musco
International Conference on Machine Learning (ICML) 2020
[arXiv, proceedings][15min video at ICML,1hr video at NUS]
- Search Result Diversification with Guarantee of Topic Proportionality*
Sheikh Muhammad Sarwar, Raghavendra Addanki, Ali Montazeralghaem, Soumyabrata Pal, James Allan
International Conference on the Theory of Information Retrieval (ICTIR) 2020
- Dynamic Set Cover : Improved Algorithms and Lower Bounds
Amir Abboud, Raghavendra Addanki, Fabrizio Grandoni, Debmalya Panigrahi, Barna Saha
Symposium on Theory of Computing (STOC) 2019
- Embed as you need: Evaluation of Random Walk and Poincare Embeddings for Healthcare Tasks*
Khushbu Agarwal, Tome Eftimov, Raghavendra Addanki, Sutanay Choudhury, Suzanne Tamang and Robert Rallo
Workshop on Applied Data Science for Healthcare, Knowledge Discovery and Data Mining (KDD) 2019